10450 Radication .ipynb

{
 "cells": [
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   "id": "a6b174d3-aa80-4939-bd35-90ee20f6483c",
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   "source": [
    "![image.png](attachment:73517cb3-98da-4c40-8d77-21db4972fcb9.png)"
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   "id": "0db8117a-6de9-4b6f-b50b-f9b61806b2dd",
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   "source": [
    "#### Library :  Libaldo.py\n",
    "* This library include:\n",
    "  * sympy.py The best symbolic math library for me\n",
    "  * numpy as np, matplotlib.pyplot as plt IPython.display  \n",
    "  * libaldo_math2.py this module have some util tools for classic math functions  \n",
    "  * libaldo_algorith.py some algorith to manage simple math functions\n",
    "  * lib_MyEq , this module manage maths Eq\n",
    "  * lib_MyEqEq , this module will be MyEq=MyEq\n",
    "* Also include the most used variables like   ,x,y,z,alpha,mu..   etc... mayby 150 variables  "
   ]
  },
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"
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   "source": [
    "![image.png](attachment:54df9e1e-714e-4371-a5f2-ffb26663218e.png)"
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   "cell_type": "markdown",
   "id": "627e9975-5498-4e46-b0ba-2a605806f638",
   "metadata": {},
   "source": [
    "![image.png](attachment:73517cb3-98da-4c40-8d77-21db4972fcb9.png)"
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"
    }
   },
   "cell_type": "markdown",
   "id": "5ed4e124-782d-478f-a72d-8c817cc70265",
   "metadata": {},
   "source": [
    "![image.png](attachment:bb9ef712-ef51-4c53-8940-d517390b6099.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d3e141bf-31aa-431b-b01c-8026dc43a850",
   "metadata": {},
   "outputs": [],
   "source": [
    "# if sqrt of P(x) is exact ..find (a-b)/a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3adc1e2c-14ad-4382-af38-02a029ab9fdd",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('Libaldo')\n",
    "from  libaldomath  import *\n",
    "# this cell will be initializing your variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5e93a454-a9d1-44d6-8959-36b92239125c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle P =a x^{6} + b x^{5} + 8 x^{4} + 4 x^{3} + 16 x^{2} + 16 x + 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P=MyEq(a*x**6+b*x**5+8*x**4+4*x**3+16*x*x+16*x+4,'P')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b7569b2b-68d3-4c64-8a71-735c17b49577",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle R =\\sqrt{a} x^{3} + m x^{2} + n x + 2$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "R=MyEq(sqrs(a)*x**3+m*x**2+n*x+2,'R')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7aae51dd-7299-46c6-a578-a7827d6cd75e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a x^{6} + b x^{5} + 8 x^{4} + 4 x^{3} + 16 x^{2} + 16 x + 4 = \\left(\\sqrt{a} x^{3} + m x^{2} + n x + 2\\right)^{2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# then \n",
    "Q=MQ(P,R*R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f86b751f-75b8-4968-bb67-7347c6fd68ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a x^{6} + b x^{5} + 8 x^{4} + 4 x^{3} + 16 x^{2} + 16 x + 4 = 2 \\sqrt{a} m x^{5} + 2 \\sqrt{a} n x^{4} + 4 \\sqrt{a} x^{3} + a x^{6} + m^{2} x^{4} + 2 m n x^{3} + 4 m x^{2} + n^{2} x^{2} + 4 n x + 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q.expand()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c781ac69-b052-49a8-a712-b904e05bc347",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a x^{6} + b x^{5} + 8 x^{4} + 4 x^{3} + 16 x^{2} + 16 x + 4 = 2 \\sqrt{a} m x^{5} + 2 \\sqrt{a} n x^{4} + 4 \\sqrt{a} x^{3} + a x^{6} + m^{2} x^{4} + 2 m n x^{3} + 4 m x^{2} + n^{2} x^{2} + 4 n x + 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# simplify sidem terms\n",
    "Q.simplify()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "da021ebc-d04e-4428-8439-a5f3cd4be612",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a x^{6} + b x^{5} + 8 x^{4} + 4 x^{3} + 16 x^{2} + 16 x + 4 = 2 \\sqrt{a} m x^{5} + a x^{6} + 4 n x + x^{4} \\cdot \\left(2 \\sqrt{a} n + m^{2}\\right) + x^{3} \\cdot \\left(4 \\sqrt{a} + 2 m n\\right) + x^{2} \\cdot \\left(4 m + n^{2}\\right) + 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q.sortdegree()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4367b448-2ec3-4b2a-aa79-4bb8c721d8d6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "veccoef=coef_list(Q.L-Q.R,'noncero')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "38c65727-9880-4223-a7a4-2bfdea954538",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a =1$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle b =0$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle m =0$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle n =4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a,b,m,n=simplesolve(*veccoef)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7f2209a-8ae5-465f-ae09-e1e681588963",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAAgAAAAOCAYAAAASVl2WAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAZElEQVQYGWP8//8/Aww0NDQYAdmrgdgYyP4AEmcBMgSA9GwgfgfEJkCsBMRwAFIAUhkKEgGyy4AUyBQ4YIKzcDBGFUACBj0chKHhJQQLN0ZQZAGDGBRBIOACxKC4OQfE94B4NwDm+hiAOyllRAAAAABJRU5ErkJggg==",
      "text/latex": [
       "$\\displaystyle 1$"
      ],
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(a-b)/a"
   ]
  },
  {
   "attachments": {
    "73517cb3-98da-4c40-8d77-21db4972fcb9.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "7915abea-cd0a-4310-858d-643254ed3864",
   "metadata": {},
   "source": [
    "![image.png](attachment:73517cb3-98da-4c40-8d77-21db4972fcb9.png)"
   ]
  },
  {
   "attachments": {
    "b9f604b0-508a-45af-af29-a1329ed404b5.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "5907a4aa-862e-43e6-9566-e0e02cd890f1",
   "metadata": {},
   "source": [
    "![image.png](attachment:b9f604b0-508a-45af-af29-a1329ed404b5.png)"
   ]
  },
  {
   "attachments": {
    "7e3f6ff9-4fe9-4c61-92a7-82537961a11c.png": {
     "image/png": "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"
    },
    "b6d88172-34b2-448b-85a0-93730f556dba.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAAAFYAAAAwCAYAAACL+42wAAAH6klEQVR4nO2af0hT3xvH39t0zpw6dc2VSmqlpaVERSEUiIiYDJOkJNDKSJT6R0IKTSFCTDFKoaKUDGMqRTD6QyyWgkiFiZg/amZoC3NCU6ai00l7vn+E+7p2t93Npp9Pn73gwPac5znPue9zds7ZvZdDRAQ3fxzuRnfgb8UtrItwC+si3MK6CLewLsItrItwC+si3MK6CLewLsItrItwC+siPDa6A79DRJiZmYFIJHIoTq/XY3Z2FgKBAB4evy5Lp9OZ+YhEIgvbarhcLoRCIWZnZ23m8vPzg6+vr02fNQtbU1ODqakpVr43btwAAJSWllr1MRqNePnyJVJTUx3qh0qlwqtXrxAbG2salNbWVjOfY8eOWdhWw+fzceTIEbx+/dpmroqKCly9etWmD2ctd7dGRkaQmZmJyMhIizqFQmH6fPz4cSgUCqyk4nA4ZnX/RHx8fJCUlIQXL16YbFVVVfDz84NQKISPj4/N+DUJW19fD6VSiZaWFsuGORwLIVd/Z/r8N7GmpSA6Ohrp6el/pCN/m8BOnwrm5+eRkpKC6elpxnoispip1lgRdfUS8W9nTTPWy8sLnp6ea+7ERs1UtVqNpaUlh+PEYjECAwNtO5GTPH78mAoLCxnrAJgVW6yuX0N3HKarq4vEYrFFX9mUiooKu+07PWOVSiU2b95sYWfatOwMrLNdWBMfPnxAREQExsbGHI7l8/l2fZwWViAQ4NKlSzZ9yIF1cz03L6PRiObmZly5cgVCodAlOZzevHg8HuP59XcxN2pG2oPH42HHjh0ua98pYd+8eQO5XG613pGZuhEQEaKjo7F3716X5XBqKSAiFBUV2fQZGBhg/fNe7zNsZWUleDweuFwuDAYDsrKy8P37dwCARCJBSEgIAGBychIajQYFBQVISUmBVCplP2Gc2VELCgqosbHRps/WrVspNDSU1U7vZDecwmg0Ul5eHnV2dppst2/fJgCUm5tLb9++Ndl7enpIJBIRADpw4ADpdDrWeZy6oqSkJLMO/M779+/J39+fRCIR9fT02BRuPUUl+iUWl8s1s60IK5fLGWNkMhkBoKdPn7LO4/Aa29LSAiLC4cOHGeuXl5fx8OFDBAQEQKfToa6uztEULqe4uJjRbu3oVVJSAgBoampincNhYbVaLRYXF63WT09Po66uDk1NTYiLi8ODBw8cTeFSGhsbERYWZmbjcn/JUFVVxRizZcsWAL9OEmyxKuynT58cGqEVOjo6cPDgQezevRvZ2dkAbB+5iMUJYnx8HMPDww73hYmRkRHExsaa2Y4ePQqJRMLoPzY2hrS0NADA3bt32SeytkaUlJRQXFycmc1gMJBUKqW2tjara0tGRgaVlpYSEdHk5CSFhYWRr68vdXV1sV6ffqejo4Oampqcjl/h2bNnlJCQYGHXarUUERFBmzZtos7OTrMSHx9PYrGYBgcHaXl5mXUuqzO2uroa3759g1KpNLNrtVqEhoYyxvT39+Pz5884ceIEACA4OBg5OTmYm5uzehfMFRARHj16ZGHX6XQwGo0W9qCgIHh5ecFoNEKtVpvK/fv38eXLFywuLmJwcNC0ZLDtBCNpaWkEgO7du2eyGQwGunjxotVRamtrI4lEYmZrbW0lgUBAkZGRrEebiGh8fJyqq6upurqaCgoKKDc3l3Xsx48fKTU11cJ+8uRJ6u7uZozZtWsX+fn5MdbV1NQQAHry5AnrPlgdArlcjvj4eDObSqWyOUhlZWUwGAxob283FS8vL/D5fOj1eqjVatYDHhgYCJlMBplMhoSEBIf+JaWnp0OpVKKhocHM/vz5c9ZtrOb06dMIDw9Hfn4+Ojs7WcVYFdbf3x/e3t6or683/Xzu3LljtSGFQoHh4WFwOBxkZmaalZ8/f0Kj0aChoYHxp8iEt7c3oqKiEBUVhdDQUAQHB7OKA4CbN29i586dmJiYMG2cCwsLSExMxPbt21m3s4JYLEZ2djbm5+exsLDAKsbuotHb2/t/Zy4XycnJjH4qlQplZWWYnp62KO/evUN4eDiuX7+Oubk5lpfjPBkZGZBIJLh27Rr0ej0AoKioCNu2bbN/g/oPYVPYmJgYAMDQ0BBmZmag0WgYn3HNzMygsrISGRkZjO3s2bPHFGftcG6LgIAASKVSh2LKy8stbCvX4yjt7e2ora2FRCKBWCxmF2RrAe7r6yMAdOHCBeru7qaAgABGv/LycgJAo6OjVtvq7e0lABQSEkIDAwOsNwFnUalUBIA0Gg19/fqVIiIiGI9LRqOR5HI5CYVCEgqFNDk5aVbOnTtHUqmUfHx86MyZM6zzsxJ2//79pFAoqL6+3sJndHSUYmNjCQDV1tZabSs5Odn0aOPy5cusO+gsP378oEOHDlF2djb19/cTAEZhFxYW7D6KOXXqFHV0dJDRaGSd3+Z7BWNjY0hMTIRarYa/vz9u3bqF8+fPm/ksLS1Bq9UC+PVUISgoiLGtqakp019hDw8PhzYjZyksLERfXx/0ej1kMhmKi4st/uURESYmJmy2ExQUBIFA4Fhye8rn5+cTAPL09KTm5mYH5szGMzQ0RHw+nzw8PKihoWFdc7O+0R0fH4+srCzHRm2DiYmJAY/HQ1RUFM6ePbuuue0et/bt27ce/fjrsCtsXl4eOBwO+2PGP4zw8HCr9zZcCauX4qqqqpCTk+PwWfK/zJreNnRjHfer8i7CLayL+B+8v4JwCI1kHQAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "8dce85ad-3cb2-4347-b864-86a99927c572",
   "metadata": {},
   "source": [
    "Descompone this :    \n",
    "![image.png](attachment:b6d88172-34b2-448b-85a0-93730f556dba.png)\n",
    "Like simple Radication if : \n",
    "![image.png](attachment:7e3f6ff9-4fe9-4c61-92a7-82537961a11c.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1f09a613-ee6c-4514-8bf2-8deda3dd1f78",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('Libaldo')\n",
    "from  libaldomath  import *\n",
    "# this cell will be initializing your variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3748a696-8c90-4d38-845e-6898c7feab0c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\sqrt{A + \\sqrt{B}} = \\sqrt{m} + \\sqrt{n}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q=MQ(sqrs(A+sqrs(B)),sqrs(m)+sqrs(n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b7f9c70d-ec04-453b-8ffb-f6fe99711a53",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A + \\sqrt{B} = \\left(\\sqrt{m} + \\sqrt{n}\\right)^{2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q.Pow(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e9e88b5b-2bc1-45cf-80bb-46bfccd33a3f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A + \\sqrt{B} = 2 \\sqrt{m} \\sqrt{n} + m + n$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q.expand()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a00dbdc8-7a4a-45a3-b02a-a74544806486",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'A' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[5], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mQ\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfactorexpo\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mD:\\Libaldo3\\AAAA Math Biblie\\Libaldo\\lib_MyEqEq.py:2961\u001b[0m, in \u001b[0;36mMyEqEq.factorexpo\u001b[1;34m(self, *args)\u001b[0m\n\u001b[0;32m   2958\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mright\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m args: \n\u001b[0;32m   2960\u001b[0m     p1\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mleft\n\u001b[1;32m-> 2961\u001b[0m     sp1\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mstr\u001b[39m(\u001b[43mfactorexpo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mp1\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[0;32m   2963\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39me1\u001b[38;5;241m.\u001b[39mksym\u001b[38;5;241m=\u001b[39mparse_expr(sp1,evaluate\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m   2965\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mleft\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m args: \n",
      "File \u001b[1;32mD:\\Libaldo3\\AAAA Math Biblie\\Libaldo\\mathexponencial.py:208\u001b[0m, in \u001b[0;36mfactorexpo\u001b[1;34m(expr)\u001b[0m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfactorexpo\u001b[39m(expr): \u001b[38;5;66;03m# simplify each exponent  in expr\u001b[39;00m\n\u001b[1;32m--> 208\u001b[0m     kres\u001b[38;5;241m=\u001b[39m\u001b[43mcorefunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexpr\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mfactorexpo\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m Is_Pow(kres):\n\u001b[0;32m    210\u001b[0m         kres\u001b[38;5;241m=\u001b[39mgetbase(kres)\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mfactor(getexpo(kres))    \n",
      "File \u001b[1;32mD:\\Libaldo3\\AAAA Math Biblie\\Libaldo\\mathexponencial.py:39\u001b[0m, in \u001b[0;36mcorefunc\u001b[1;34m(expr, kfunc)\u001b[0m\n\u001b[0;32m     37\u001b[0m     kres\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m\n\u001b[0;32m     38\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m expr\u001b[38;5;241m.\u001b[39margs:\n\u001b[1;32m---> 39\u001b[0m         kres\u001b[38;5;241m=\u001b[39mkres\u001b[38;5;241m+\u001b[39m\u001b[43msfunc2func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mi\u001b[49m\u001b[43m,\u001b[49m\u001b[43mkfunc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     40\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m Is_Div(expr):\n\u001b[0;32m     41\u001b[0m     p1,p2\u001b[38;5;241m=\u001b[39mfraction(expr)\n",
      "File \u001b[1;32mD:\\Libaldo3\\AAAA Math Biblie\\Libaldo\\mathexponencial.py:24\u001b[0m, in \u001b[0;36msfunc2func\u001b[1;34m(expr, kfunc)\u001b[0m\n\u001b[0;32m     16\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m'''\u001b[39;00m\n\u001b[0;32m     17\u001b[0m \u001b[38;5;124;03margs:\u001b[39;00m\n\u001b[0;32m     18\u001b[0m \u001b[38;5;124;03m    expr=math exprssion\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     21\u001b[0m \u001b[38;5;124;03m    kfunc(expr)\u001b[39;00m\n\u001b[0;32m     22\u001b[0m \u001b[38;5;124;03m'''\u001b[39;00m    \n\u001b[0;32m     23\u001b[0m sexpr\u001b[38;5;241m=\u001b[39mkfunc\u001b[38;5;241m+\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m(\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;28mstr\u001b[39m(expr)\u001b[38;5;241m+\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m---> 24\u001b[0m expr2\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;43meval\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msexpr\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     25\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m expr2\n",
      "File \u001b[1;32m<string>:1\u001b[0m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'A' is not defined"
     ]
    }
   ],
   "source": [
    "Q.factorexpo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ceea58c1-7c23-4d3f-9925-e3b54b3de5fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A =m + n$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle B =4 m n$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# then\n",
    "A=MyEq(m+n,'A')\n",
    "B=MyEq(4*m*n,'B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6b3f50d8-9a75-4d61-9f59-b9c7c3b5ecc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle 4 m n + 4 m + 4 n = 4 x^{2} + 8 x - 16$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P=MQ(4*A+B,4*x*x+8*x-16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "86834a2d-151b-4ec5-87f3-50211f00d145",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle m n + m + n = x^{2} + 2 x - 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P.Div(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "27877368-9db7-4516-94e2-44c6116574e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle m n + m + n - 2 x = x^{2} - 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P.Substrac(2*x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "16b81b27-8dbc-4567-b0e4-36def90a79be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle m n + m + n - 2 x = \\left(x - 2\\right) \\left(x + 2\\right)$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P.factor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "307c7bcc-2aad-4784-a9e0-c260f4fa5de7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle m n + m + n = 2 x + \\left(x - 2\\right) \\left(x + 2\\right)$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P.Add(2*x)"
   ]
  },
  {
   "attachments": {
    "c661d4bb-6b12-4dda-8bc4-2e240f974b8e.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "2f729f54-cd88-4cdc-9da3-1a3919aecf6a",
   "metadata": {},
   "source": [
    "![image.png](attachment:c661d4bb-6b12-4dda-8bc4-2e240f974b8e.png)"
   ]
  },
  {
   "attachments": {
    "a671c627-22c7-4a45-b2af-ac327cabcc6e.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "6340ac63-50eb-4b3b-9435-c1bc05183d5d",
   "metadata": {},
   "source": [
    "![image.png](attachment:a671c627-22c7-4a45-b2af-ac327cabcc6e.png)"
   ]
  },
  {
   "attachments": {
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   "cell_type": "markdown",
   "id": "e0b54b3a-a524-4a78-9b93-bdca1899d7f6",
   "metadata": {},
   "source": [
    "![image.png](attachment:73517cb3-98da-4c40-8d77-21db4972fcb9.png)"
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"
    }
   },
   "cell_type": "markdown",
   "id": "0ac84037-2768-47ef-a254-88c8d3ffb685",
   "metadata": {},
   "source": [
    "Find A and B if :\n",
    "![image.png](attachment:7a926055-b5ac-46af-a936-47a18377ab4e.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "026878cb-403e-4ff5-be2d-1e10f200161c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# This scrip initializes all variables. \n",
    "import sys\n",
    "sys.path.insert(0, './Libaldo')\n",
    "from Libaldo import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "972d0f7b-f2b9-44fc-8e46-afa53a3f8d16",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('Libaldo')\n",
    "from  libaldomath  import *\n",
    "# this cell will be initializing your variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "96cd86f9-c7eb-431e-88ab-7c2a6f0ed67d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle P =\\sqrt[4]{8 x^{2} + 24 x - \\left(8 x + 12\\right) \\sqrt{x^{2} + 3 x} + 9}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle Q =B \\sqrt{x} + \\sqrt{A + x}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P=MyEq(sqrs(8*x*x+24*x+9-4*(2*x+3)*sqrs(x*x+3*x) ,4),'P')\n",
    "Q=MyEq(sqrs(x+A)+B*sqrs(x),'Q')"
   ]
  },
  {
   "attachments": {
    "0e5a258e-add0-4b9f-88a6-f50affb876fb.png": {
     "image/png": 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VrMCO9joM92+GDM0rW1diwJzfScn/fGFMzMZ80c2+Zh/KJhUJhbrCXKr3j3pbFIC7YpfxZpO4hju3HFioGUwZGK4xQfUw0kKJSAQCX4c5+tteXA0vwuDMrLWpQODc+Qmvi8floakHMFn0cPC1OuScMrLD0OL8lIn2hTWVAvJK+s5EJrxWyYEFmdmEwyAvDCNlyDjWK6w42YltSwUMjs42K48ARzaMBKrI+U52FRswvFRF0S/zsbVFCLtziGTnQntqc0fTiVMPuvwyWi5E8O0cHXwogLPdju8uM65naphqtO6hci8ND3pRdGYaXzXTKy3g0GMvwKBf+8wiSwwAMpfCcHNFOy5T0ZcorkHY7Hkao62f7fdJyMs72dp6GfVtG6M5IfMbK2AsrsN3BVy76hNeF40VkGUDrF4ybpslTUCT5pY3/BbKetZChhH7/Qo+rHw7h1qr22Cl7xqoexIb2/litKZKC9CyqRoj1ZQ9Y2bztl1I2bmY75Gwv7QL16bYvnCu62ZtF5i7DyPnO9myGsLHOqndY8Mq+6ja6wC9loY60XubLuK7yteaiK5vt1yAynU5pDsf+BBw6IH0bGXnLAT7y52g01ypa2Sg3AxN4xvjNQ9biKCj9sPxjWddIZQ1deG7YaT4n2pw5rxL2XOvIN1jwrJK4vrRRiofCPLtkbsKHH/GRVnPZnIXGjH8ZjvHQzKt5Vu1s/2peyZ2wDnUBnLiqMlQqQFKQzHHk/FwmIGyf23A9x9GKh+r4dbZxisVCpH8XRRXeMeM3idLC7DP34FuvRnpHpmnf+GbUjvJenu0dyVz3GuysicObElWXwBOu1WMT/jRZRhpDevwVlRMWv5068BUiQ7oArKZ4sdbJv1M7dlZEwyrR6kehLJz3bDaiEkH7N4CB8cabnspoDfxfk+EyZQ3TqfR6mkEQ5znE8UkQyjk5GZY7QgBIC+zBS2SZ3L4gcqXvHS85MVzxg16C2ajjCvB0sR0dBNmVj9VoGCTC3d9BOMjdqrWK1SdaSMcgU+7AygRFSQDZy8S997STXzDbRitgBMvN/l2wmODNXsH8PmvYpICIBuQAUv+SlqbEn/PBOjuLdLW2fafTnidGSg70ExENlJ8sA8GXdQMgu/tYo70NiAtt7J5lUTlbkfczUlcg1B27jSsNnJVp6Nyaysz4VK7DATOXQQ5tiayIXsRLNQR+DoC4VhdmKqHQwHc7Xb8mVZtzfaWDrgMMFW+ghqW6XlKgadGix5kafkmKEDPyYeAHur7wrTu3BDzN3rfaKFo/T4WoENd8P2Y8+ORrLdH/fcpfyWG6epL9SBsOduNlBOtHhZb6S8R6dSBZPA0mrm6dh8ljg4t5mGG6Hu3htzVZUhIVD1o5NDBsedNpVUE0XHorcm/h9M1WpPl/EXgXOzzy5JA1hsI34DLF1S+rReatifXz3sBf6cNY7ll3OCt6egmzLx+qsCGXYdh19hg3q5aBdb3EAFq3p0bHs4Yw+0AyL5lffv07BjtKmDzyWaSieBL1JnHo8QNuLWcbE8pmBsHAB2b/0FH6zjbYT5ZAGQbb24qkjhq23rzOhVg/6gx8AJHH6ukrMeIlGHEkqPE/Usq4O+qxrh6C2RIcH1StzVlWoHWn8TvDEO9DbDcSt6HKlRMPwjO02jm8tp9bHi8JWZ9XgLIAEUmYdU9CTCs0gE6sn4f+0IqgKncDui04i5mI7UHYy5LyEx6e6JBMImYrr40FIJ0r5ZVkKsHCp6ErsktZ6VTB6ZKW4XCohI3G5y9qG9M7dlcvjY1A/Gbg5D7VC/IJorukzikrxtZS68CpNUP0XsReGvyM6/pGq3Jsu0gcDD2+bSVg6l2iE+vyRQ/cJhUzxqvfgkQ5lJYJpEreTq6CbOjn1bA+EgdINExCBxMvDyTTmLyuI0lwEItXzBwDWianRGGAhhWrcCwyjDlT9ay5MqsHn8LCH4KgEEHFCQur2ksNQEKLn+A8Uaqmu2Jv61m9SAwpLnJEm3bZwZWFDYA0kjAzHymp9EMliPkPX48ZtZUVQjvPuEgc1kxmZmZMR+fIxMIEwAyM1vIzMyM6/56pULh8tpdqCc002ZaJXFzSDrrhL/WOqpFC+FmDOsYpqMvZmDzcw20nsqCa3039SV9dbtnirYKhTU1XWxwfhpT/rNMD+bd4z/b1uDUCkG5gGCfpjvGDFBso4WBig4osDCX1/tUppJLH9do3UYs+lsAme5z8eN95qNuRpdm0JkJRMC2r4W5EkAYY7iju1wBnP8aZqu4fSWQmZkXtwOf6JPsWlsrEPxYi9odT7EUQDFatCo7b4+/PtXtBq4FtMjEvWO9ByYASda27TsVf9s+Z6OZ3szNRHq0juTJHIX5Wg+464AZLG5KdsS6Osv0sONAM2rW9O7Nrod1la9Q7blM9z4bECB3IZgai7DrofNMG9w3sxW1xkP1AqjIGYA+K+b8dPQlqiu2n9YT/vg3ADxboAB2ehrNWI/MnVrLk8VTobDmZ51sOhhrtM2A4zUnkXtjN7dYASAv0Yqqnpq619D3qxZG0i/XGwETClrutv8G+PZPvgOfj0YrHuYcKCqxgH7sO2oGjBvcBCJwqCE26wHmn24qQNubZcj5+whEoGRH64wuz0yVMYZb20Zu9CXQCqsk5ypX9MDC+DOHucxAdyvRsprW1fGNpF0PLDPiv8i4OZyguV0DbfVIRGh7Ihf0o8FJjt1GyDZx/EIkrgumoVCrDVz8Yi+9HTYgjCkbKH+WhkJo7u3hZvLenKfzOTNGmxvlLpmel4sY/mJ4zKeuZ5jA3UWwf+o1ATylEAoNMDAUwnlygOPBdfh2VnNoEDirzYrcFgO73uun/tQSODN7Fdhe7wIG+0bzRb/FVPRFAYb/r5PhUIihzwbIKvVQ/GIv4OL0MRcQxCRD/ye7uGR20/LLubM1ZFYpRD0LSkZ8b1PzEwrmn7Wx4C4dnZXrYnTGExzmao4dX3OsVzBaH+DTIOCJb0zGo+Xmc4LRGbKjAFiej/eTSMI0tHjMN6MVjyLA82YzzU1uBk62YT3QBhix5oD7/TrUv7GMiT2Yz7ppz1foOulG2VRH67nr5P2kGvXt2SvYFI/vAjTsNtPc5Kartw2WjxqCHbk63E0eHE1uJmsg7AXQeayOsg/6IUMbVe7Kl2lu78de72auzxa9TUBYc5cb9cTdqm7tk0CGkY7P40f2fpu8Ci+tezawJuJn6OQ+ek72M/BJD4qtk2qPSuW6DURdMF21CqHQMAMDw1iPDFF/KguairVAueBpZKC/2sRDTf38vOUSc2m7v0S0lUNuhRuQkTJAWijFfMiQki4defkrIHIVnQwdF2Uqt9QAPlSgZX81RALIEtR/TMo2bUgWH+D/bS0SYM+Lv6QzWX1RgetXtPKoEZ0OW2MfNGmz0uq3INjVCEBYlineeTypCP1U4yiFnvZmzPVaLAlAZ7GC+1gX1prRrRMbCqCoVtv0YTydSbQrV7Tyo7ZH9tSrEkafE2hGyPrUOkxPWYmgUOsd38s2n41WIjoA/4kWiITRSdBgMzEc7GLHsWHqPzeQ80DxmNiD+aabJsBTb2fok052/boHXziXgopD2B5YBv2zW3kyHt9ZvHjxX2ZbiLnG8HtVSHnaulmO24+6p2Ds+fcdhO+rYmW5FzypNQTRIBKQcfUEqflJBVGj3lahYKrpJIwO2xt+vN+Sa6YY/qAODFtY6jkPu9LzN29nrEDDgAd/ppmCvMNTmr3NFvNJB6JpQ74bJoqX15BsIJYTsAe7IMNIIAwGAngjBkpWVjLRgHnoHTtygZPgDaho6sP7Cy1YVgE637GjK3DiD0NB+WE4MfPP32MDU00/vitLKPn7GsYLqJ2PTFc/FcCwyYS3/SqznVM+GYThjkPnXsjdPQxIuM5CzY9Hc3MdQNUXnXiv5U7qBRYI4hEdoNV0g2tTAbdzymW66X/TzKJNHpY5fCOzvGS5dRAPUNyu4nt84hrqAsFMknB3sDuZ0/uBG1pKQ/4quLVYQbSqnO98GGG0BclS3AR+t41d94Nx9yuzLc5tQ1uFwqKH3WzaP32jDdDbcYhozIu2de/cyOMV3NkIwx2HGoBz3QCsyAD2jqaDrCm0a7W1P4ofBS4QTJaCPV4CTTbad6/EuLtttsWZ97TtNqI820mB83TMntHJEo0tARKupwsE6UYY7gT4T2lrQBLgeFALsrOgbWfqv0bcqlUCwVTZ8Asvr25YyeacMHM9cHMuYwGCOWXk/LQetTF1cSctgNqtrZFXf+RHLGkI5gJijTsBDXqwntHqVfvCULysBk+JC3PTAK6zujHr3gKB4PbFpAcpt+jmrnJzP3BJcPsTt1a5AFoHwTroB71hZNMRw9qzgI6aj8TLKxDcKfgGgcH5s3uX4PZHuMoT4APUs1rwmQzYH1yJstpKAOB1YbgFAoFAMDsIwz0O/mYf0TWtCqMO9CZOXwAGp14kRCAQCASCVCAM9zh0dAFBLXpcpwPQ3fbbnAoEAoFgbiMM9zi0AkH/6NqWlscp3OQCgUAgmD2E4Z6AgQ9biBZgCASBLhGkIhAIBILZQxjuCbh105EOf5BkNiwQCAQCgSBVCMM9AS4gcq6bMNDy4cBsiyMQCASCOxxRgEUgEAgEgnmEmHELBAKBQDCPEIZbIBAIBIJ5hDDcAoFAIBDMI/4/KNNtoDZgGewAAAAASUVORK5CYII="
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"
    }
   },
   "cell_type": "markdown",
   "id": "ebdeb419-2bde-44bd-aff2-1134458d831d",
   "metadata": {},
   "source": [
    "try to Find ![image.png](attachment:98ee898a-a2a4-4f23-824e-efe81299cc10.png) in...\n",
    "![image.png](attachment:0e5a258e-add0-4b9f-88a6-f50affb876fb.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "a0d85140-a9bc-4244-8b45-036e8e0c9746",
   "metadata": {},
   "outputs": [],
   "source": [
    "# trying to build a dynamic expressio"
   ]
  },
  {
   "attachments": {
    "7a926055-b5ac-46af-a936-47a18377ab4e.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "fe3ad9d8-9fac-4594-98f2-e45805c32127",
   "metadata": {},
   "source": [
    "Find A and B if :\n",
    "![image.png](attachment:7a926055-b5ac-46af-a936-47a18377ab4e.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b6d2fb27-c6de-4a8e-82e9-7a227958efa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle e1 =x + 3$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle e2 =2 x + 3$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle e3 =8 x^{2} + 24 x + 9$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e1=MyEq(x+3,'e1');e2=MyEq(2*x+3,'e2');e3=MyEq(8*x*x+24*x+9,'e3')"
   ]
  },
  {
   "attachments": {
    "e1e64c48-110c-4140-ab37-dcfbb1621913.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "66a51723-f89e-463f-9f6e-79803b1e71f5",
   "metadata": {},
   "source": [
    "![image.png](attachment:e1e64c48-110c-4140-ab37-dcfbb1621913.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "91a79d22-3ad5-4616-b4ab-c868b36b300a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle e3 =4 x \\left(x + 3\\right) + \\left(2 x + 3\\right)^{2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e3.transformada('A+(2*x+3)**2','A','es')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9573b7f8-a39b-4246-8593-1a739035ae60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$\\displaystyle 4 x \\left(x + 3\\right) \\left(2 x + 3\\right)^{2}$"
      ],
      "text/plain": [
       "                     2\n",
       "4⋅x⋅(x + 3)⋅(2⋅x + 3) "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "4*x*e1*kpow(e2,2)"
   ]
  },
  {
   "attachments": {
    "a76048ec-0108-4ebe-9459-8b89560336c7.png": {
     "image/png": 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kpBCNRkkkEvh8PgYHB3nvvfcYGRlBq9VSW1tLWVkZFosFmUxGIpFgdXWVW7ducf36dYLBIMePH+e73/2uZJjRaJRHjx5x8eJFent7UalUnDlzhrS0tL0ZZjQa5dy5cywvL3P48GEyMzO3GOFODygcDhOPx8nJyeHkyZNkZmZue6yYi6fT6ZDL5VtmbUEQ8Pv9BAIBBEFAqVRu2dPK5XLsdjulpaXk5uayvLzMxMQEFy9epLm5mbS0NIlRnpycJDU1dVdRxONYWVmht7eXuro6cnJypApmT7uXSCRCOBzG5/Px8ccfc/v2bfr7+5mdnaW4uJjvfve7dHR0UFJS8tQ+iIhEIkQikS1/F937x0m1RCKB3+9HJpNhMpm2DPLl5WUuXbpEVlYWdXV12xqBVqslJycHs9nMyMgI//iP/8hf/MVf0NnZidFoJBqNMjExwXvvvUdPTw9arZZkMrlluxEIBJicnGRiYoKRkREEQaC/vx+lUimlfuXl5b3wHi0SibC4uMjt27dJSUnZccw9DeICIUYN1tbWWFtb49q1a9KqbzKZaGlp4U/+5E+orKxEq9VKz9BoNHLo0CHu37/P1NQUFy9epLW1lSNHjgCfT4perxe5XL5JOPPk/W87Or1eL7Ozs3i9XjIyMmhubsZsNhMMBvd0c+IL0mg0mM3mHeNTYuB9J988mUzS29vL2NgYFouFyspKCgoKthxnNpupq6vjzJkznDt3jomJCc6ePcvMzAw6nY7Z2VnS09N55513yM3NRa1WU1lZ+dT72NjYYGJiArVaTTKZpLi4eMdjxXuRy+XMz8/T19fHp59+ysjICNPT0ywuLmI0GikqKqK5uZnc3Nxnihv29fVRWlr6VFcvEong8Xg4f/48Go2G733ve1s0tyJRVl5evmNCtKjYsVqtDA4O0t/fj8vlwu12MzMzg8fjwev1SlsQvV5PRUXFFoPQ6/UUFBTQ3NyMUqnE7/dvGYRlZWWcPHlSurfn2W8KgkAkEsHr9e5I/u0Fjy8QfX193L17l/HxcR4+fMjU1BQulwuHw0FtbS3V1dWkpaVJx8vlctLT06mvr6e/v5+FhQWmp6dxOp04nU50Oh3T09OEw2FOnTpFQ0MDCoViixsL2xhmLBbD6XRy48YNyfoPHTr03Df6PEgmkwSDQZaWluju7mZ5eZm6ujrq6uo27d0ASX9ZXl7OW2+9xd27d7lx4waLi4s8evQIvV6Pz+fjz//8z3njjTd2dB/h83vf2NjA7Xaj0+lwOp2Mjo5KLK446ETWeKcB5Pf7GRsb48MPPyQejxMKhRAEAa1WK52XSCRIJBJ7IgwEQWBwcJCKigpOnz6943GJRAK3282DBw/4+c9/jtls5lvf+hZ6vV7yEOLxuMRIZ2Rk7LjPTUlJoaioiJKSEu7du0d3dzfz8/OMjIwwMzNDIpGgoKCAt956C61Wu6Pg3mg0UllZye/93u9RVlbG+vr6FsMsKiri1KlTe45litLHtbU1EokEJpMJl8vF4uKiNHGILLPRaMRoND4XweR0Ount7eXBgwdSGRC1Wi1V7hOr3D1e/U68XkNDA1NTU4yPjzM8PIzNZsNqtbK0tITRaOTkyZO7emCbDFPcvN64cYN//dd/5W//9m9pbm5+ppt5GYhGowwMDPDf//3fLC8vU19fz7vvvrvtailCqVRiMBhIT0/HYDDg8/lYXFzk6NGj/OAHP6CtrW3XOKAgCLjdbq5fv87PfvYzqqqqWFtb4/LlyxQWFuL1eqUVLjs7m6qqqk3hHxEymYySkhLefvttmpubcbvdDA0NceXKFcbHx7l+/Tp+v5/vf//7HDt27KXGZH0+H319ffzbv/0bk5OTaDQapqenN0kZvV4vXq8XmUyG0Wh8avWA1tZWyfW9dOkSo6OjALzzzjs0NzdLqpinoaqqiuLi4m0JvJ3i4TtB9GR+/vOf4/F4+NrXvsbAwAB9fX1SpT+RZW5vb6ezs5P29vZnZk1Pnz5NY2MjHo+H+/fv09PTQ29vLyMjI/j9fsLhMG+++SZVVVVbzi0oKJBCYxcuXGB4eJi6ujqOHj26qejWTthkmGL8cXJyEoPBgMlkQq1WS/sbn89HKBQikUhImRTiHvBlqFKSySSRSITu7m6uXLnC7du3qampobW1laampl0HsU6nw2q1UlRUhNVqxefzodPpKCwspLOzE5vNtishINY8HR4eZnR0lEgkgkKhwGw2s76+zr1799jY2ADg8OHDlJeX75j1otPpJGIrEAhQWFhIUVERFy5cYHBwkNu3b1NXV4fNZtuTYcpkMhwOx66rvfj81Go1WVlZaDQa3G43t27dwmAwSIY5Pz8vsYG5ubnYbLZd35vFYsFqtaLT6aSUvYaGBklfK5fL97Q/1Ov1L01Z5PF46OnpYWRkhKWlJeLxOPPz88zPz+PxeAiFQtIqVlFRsa37vBeI7LHoLRUXF1NTU8OFCxeYnZ3lwoULlJeXU1JSsmVsWa1WHA4HeXl5LC0tEQgEqKmpoaqqipycnKdORJsMU1TsOJ1OsrKyWFxcZHh4mLS0NNxuN+Pj4zidTikVJhaLMTo6SklJCaWlpS+stvf7/TidTrq6uujp6QHgxIkTdHR0kJOTs+u5IpOZn5+PxWJhfHyc1NRUcnNznzqgH7++XC7H4XBIqT0WiwWPx0M0GpWyRex2+1NftLiCi2lONTU1hEIh1tfXuXTpEr29vRQXF1NbW7unvlVVVT11X6xSqbBarbS2ttLX14fL5aK3t1cK4sPnxM/y8rJUNeBp+Y+ikCQ3N1cK2zgcDtLS0r6wIsyxWIz19XUsFoskVJHJZKSnp5NMJsnKypLY5vz8/GeqBfs4RP5Do9FQWVlJcXExTU1NzM7OMj4+zt27dxkZGaGxsXGLsZnNZux2u+RtpaWlceLECfLy8vY0QW16smKs5uHDh8zNzXH//n3sdjslJSXS7BQIBKQCtn6/n3/+539mYWGBv/qrv3rhJNfR0VF+9rOf0dPTQ15eHn/2Z39GY2Pjb0QIIJfLOXLkCBUVFXzve99DLpczNjbG5cuX+c53vkNxcbHkyhoMhk3ywqdBJpMhl8slBYkgCNy6dYu8vDzefvvtPbWx235QREpKClarlfLycmnf9aLQaDQUFhby1ltv8atf/QqdTrfnwbVfsNvtvPvuu5tSxcQk/Js3b/L6669Lk5g4Ob4MLa5KpSIzMxOj0YhKpSIWi9HT00NhYSHf+ta3Nu0ZtVotJpOJ1NTUXfeSO2GTYSqVStra2rBYLKytrQFgMpnIyMigqKiIR48eMTk5yeDgIGtra2g0Gl577TWOHTv23Fkfj7uv169fp6+vj/LyclpbWzl27NiurO7jcLvdjI6ObgruhsNhiZ4WY5G7Qdy4i/D5fKjVanJycqRVdDsIgsDc3ByBQAC1Wk12dvYWJY1Y6Ffsg9frxefzPfW+ROwlJ1UM14hSQLVajcfjwe/3S8TF2toaoVAIm822J1bY5XIxOTnJ8PCwtM92u93bhm5+UxCVUY/D6/USjUbJyMigoKBgx1TEnRCLxaTwSDKZlLiKx71AkbEViS5BEPD5fHi93i0e1OTkJENDQ5IwZnV1lcuXL3Py5EnpOy67YZNhqlQqTp06RWdn57bBbLHK2eLiIl6vF5PJxB/+4R9y6tQpiW0UVweZTCaVK9yNvhY/ZvPBBx/Q19eHSqXi9OnTtLW1Se5rMpkkkUhI7T45+4VCIUn1Pzo6is/nQy6XS3rQubk58vPz9y2tSBAE7t+/z+zsLCkpKbS0tFBYWLhJfyrGF0XyY7cvWImso1gF4VlKjIgutNVqZXJykrm5Odxut5SKNjc3h9frpaqqalfiR/z618OHD7l//76UKxsIBBgeHv5CSMGn4XGjeVaIXyUbGBjA7/dTWFjIoUOHNkk7ReHG45U2nrymmEk0ODjIwMCAtCC4XC4uXbpEWVkZpaWlT+3jppEhk8lQq9WSmPzJfzqdTnLh1Go1qampGAwGtFqtZDRKpVISos/Pz3Pp0iVWVlZ27MDU1BS/+MUvJNXOj370I1paWja5r5FIhNXVVXw+35Zy+8lkkrGxMa5du8a5c+ew2+00NzdjNBoldVJ3d7dU0Hg/kEwm+dWvfsVPfvITfvzjH/PRRx9t+i6H+CKDwaC0P9+NDNnY2GB8fJyxsTFcLhdGo3FH1/lJAkqtVpOZmUl5eTlms5nh4WGcTqcUphgaGmJlZYUTJ07suvUIBAJSMrPb7eZv/uZvaGpqwu/3c+3aNZaXl5/3ce0LRI9E/LTfs8Lv9/Pw4UN++ctf8uMf/5h/+Id/YGBgYNNKmEgkJNF6IpFAJpOh0+mk95hMJqWkj+npaRQKBe+++y4VFRXE43E2NjYIBoNEo9GncxRP/mE3X1yc5cV6PzabDb1ev+mczMxMjhw5QldXF4ODg9vK9uDzwSoazq1bt5ibm0On07G6usr9+/cl6R98rsCZnJykrq6OqqoqysrKePToEQqFAovFQn9/Pw8ePADgK1/5ChqNBpVKxd27d5mamuL999+XfP1n0WKaTCZKS0tJTU196h7F7XbjdDpRKpXMzc3h8Xik37xeL9PT09y+fZuJiQnMZjMnT57k+PHj27YVjUZxu9243W40Gg1NTU3k5OTsiVwT3S2Hw0FhYSFXr15lcnKSgYEBAoEA0WhUIiYenxhE+l9MGJibm6O7uxtBEDh06BDt7e1cu3aNwcFBlpaWmJmZYWlp6ZUpnqXRaLDZbDQ3Nz8XJ5FIJAgGg6ysrDA1NcXKygput1v6XRAE5ufnuXz5MoODgwBS1pRCoeDq1auSTFEkycrLy6XxOjExsSkhpLy8HJvNtmNSwp6mFkEQ8Hg8LC4usry8TCQSkb6B6PP58Pl8kluUmZlJU1OTVKJwZWUFl8vFxsbGpk4IgrBp/7KxscHS0hJXr15FqVRuWgXm5+cZHh7mD/7gD6QJ4d69e0SjUcrKyujv72djY4OmpiZaW1sxGAxEIhFmZmZ48OABH3/8MZWVleTk5DyTYaanp1NXV4fZbH7qLKxWq1EqlUSjUebm5piamqKwsFCqEtfd3c21a9eYn5+nuLiYN998k/b29m3b8vv9TE1N4fV6ycrKknICn4VEKCkpobi4GJlMxtjYGAaDgcXFRSlMkpaWtqk9n8/H3NwcTqeTcDjMysoKExMTNDU10djYSFFREXa7nfT0dJxOJwMDAxQUFHDs2DFpRf8iodFosFqtzy2CF1dcpVJJPB5nbW1NUu6IReX6+vr4z//8T+l5tra24nA48Pv9XLp0SWonkUhw7Ngx6uvrsVgsVFRUSGGyrq4uaaFKSUl5McOMxWJSSZFPPvmE1dVVEokE3d3dnDt3DplMxhtvvPHrRpVKTp48ydraGu+99x7Xr1/HbDbT2dkpHSMa+/LyMm63m3g8zsLCApcuXdrisomzuFhxbXh4mPfff5+BgQGUSiV2u53W1la+8Y1vkJubi8fjIScnh9TUVIk9czqdLCwsPNPLMplMVFZWolardyW2ZDKZpOyYmZnh6tWrLC8vMzo6Ku09vV4vbrcbm83GsWPHcDgcO36KYHp6mp/+9KesrKzQ0tLCmTNnnvmzBfn5+djtduRyueS1TExMoNPpyMnJwWQybZps/H4/d+7c4V/+5V9IJBLU19fzp3/6pxQXF0vFmNvb23G5XPz7v/87586dY25ujpWVFdrb27fNDPoyQaPRkJ2dLdU+CgaDUtx5bW2N9fV1XC4XCwsLyOVyKisr6ezsJBAI0NfXx8WLF8nPz6e9vZ0//uM/xmKxYDQaJfH/1NSUlFEyMTFBMBjcNb92T4Ypk8kkwbNOp5M2wEqlkpqami2DRqFQUF5eTk1NDZ988glDQ0NSdQKx5o9MJsNsNtPU1MQf/dEfPbUPSqWS5uZmioqKyMjI4OjRo6SlpRGNRikvL6exsZGSkhIpC7+mpoZvfvObVFdXE41GaWhoeOYP5ew2VLIAAARLSURBVCiVyj3tV2QyGZ2dnUQiEbq6uqSMirt37/Lo0SMpy72jo4PDhw9z7Ngx7Hb7JjJK3IeOjY3R09PD2NiYJMbOzs7eVmW0GzQaDQaDQdprB4NBFhcXpcJfT9YQEnW8x48fRxAEKisrqaiowGw2Sy5vaWkpp06dkgZUQUEBDodjxwyVLxNSUlIoKSnhxIkTxONxent7cbvdBAIBgsEgwWAQuVxORUUF5eXlHDt2jIaGBqngWjAYJD8/n8bGRhwOx6bylg6Hg1OnTkmLS0FBAZWVlbsWltuTYSoUCmpra7Hb7VvKYaSmpm4xTJlMJsXTDh06JAVja2pqpKK+SqVSSpPai6BcJpNJSgyDwcCZM2dYX18nFothMpk2BbxFAbZer8fr9RKPx7ft58uCXC6nra2NlJQUEokEHo9HylMtKyuTSLFvf/vbHDlyRBLSi/B6vRIDe/36dT777DMikQilpaXk5+c/dwJuSkoKxcXFTE5O4nK5cLlc1NbWbks6paenS3tZ+NxbsFgsm9LdsrKyaGlpkcT8JpMJu93+hX/t+WVAp9NJObXipyKerHKRmpqKw+Hg2LFjVFdXY7PZsFgs2Gw2amtrycjIwGw2b6k5K+Yki1k0BoNB8mZ2gkzYo1ZJFD8/GUYR1RFPvpxkMsnDhw/p6uripz/9KS6Xi6qqKn74wx/S2tpKdna2RC3vtcyHUqmUrifmyQmCsGMfnjxGPH8/IJIHHo9ny3N6vJ6PyFiLfxMEgUuXLjE0NMT6+jqXL1+WxPc//OEP+drXvraniWs7PHz4kHPnznH27FmJsPjrv/5rvvOd73D48OFNA0MMSYmhLbGe7+Os73bHPIvQ4ssAMSS0ndhe/IS9GKEQv1qWSCSIx+ObxueTEBO54dfPbTfsearbq1snQi6XY7PZaGtrY3V1lQcPHhAMBhkaGpIkTlarlZSUlOciDvZyzm+SkFAoFFsECnvFwMAAV65cweVy4fF4KCkp4etf/zodHR1bsmmeBaKk8HE2t6CggMLCwi3GJLK5u8V693LMlx1iBtDTVFYiREN82lgTxR97xb76IOIXeMXNspg1Pz8/L6lT9rvWzKsOMRFAzG8sKCjg1KlT/OAHP3juSUvE4/muWq0Wo9FIXl4eWVlZ+1oN7wAvjn3fHCgUCsrKyrDb7RIrq1Kp0Ol0+16Z7csAmUzGN77xDRobGwmHw2RmZpKXl4fRaHxht1tUAWm1Wux2O21tbfvypegDvHzsu2GKYoQvUvT8KkNM6crNzSWZTKLT6dDpdC+FUDGZTFRXV2O326VM+ZdRZe8A+48vP532W4C0tLR9KWJtMpkwGo00NjZisVik74Yc4NXHnlnZA3x5sby8TCwWkzTPX7RK5wBPx4FhHuAAryBejS+5HOAAB9iEA8M8wAFeQRwY5gEO8AriwDAPcIBXEAeGeYADvII4MMwDHOAVxIFhHuAAryD+H2UAJrZRVrDCAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "2a25954e-cdc1-4b38-b10e-f440a61a84fb",
   "metadata": {},
   "source": [
    "![image.png](attachment:a76048ec-0108-4ebe-9459-8b89560336c7.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "28bc2b48-cf88-493d-8d61-6a94e364df9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle e4 =4 \\sqrt{x \\left(x + 3\\right) \\left(2 x + 3\\right)^{2}}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e4=MyEq(2*sqrs(4*x*e1*kpow(e2,2),2),'e4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "78f5e579-01c9-4579-a91c-53cd91aecaf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle P =\\sqrt[4]{4 x \\left(x + 3\\right) + 4 \\sqrt{x \\left(x + 3\\right) \\left(2 x + 3\\right)^{2}} + \\left(2 x + 3\\right)^{2}}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# then..........\n",
    "P=MyEq(sqrs(e4+e3,4),'P')"
   ]
  },
  {
   "attachments": {
    "98ee898a-a2a4-4f23-824e-efe81299cc10.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "ecaf3c14-4ca0-40c2-9f2e-fcbe7103af6e",
   "metadata": {},
   "source": [
    "![image.png](attachment:98ee898a-a2a4-4f23-824e-efe81299cc10.png) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "47586c7e-4256-47f6-89c4-fd25bdb8d5f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle a =2 \\sqrt{x \\left(x + 3\\right)}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle b =\\sqrt{\\left(2 x + 3\\right)^{2}}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a=MyEq(sqrs(4*x*(x+3)),'a')\n",
    "b=MyEq(sqrs((2*x+3)**2),'b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4bb2a22e-762c-41bf-b110-a370994dba31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle b =2 x + 3$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b.killsqrtpow()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "cb4b6409-b1e5-4184-8ccb-062fbe9e17b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/latex": [
       "$\\displaystyle 2 x + 2 \\sqrt{x \\left(x + 3\\right)} + 3$"
      ],
      "text/plain": [
       "          ___________    \n",
       "2⋅x + 2⋅╲╱ x⋅(x + 3)  + 3"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a+b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "aaa337b7-c7b1-4a56-8092-edc9d0dbfb74",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle P2 =\\sqrt{2 x + 2 \\sqrt{x \\left(x + 3\\right)} + 3}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P2=MyEq(rpow(a+b),'P2') "
   ]
  },
  {
   "attachments": {
    "98ee898a-a2a4-4f23-824e-efe81299cc10.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "e603e9c7-7f08-4c5a-b153-2cf14a084d71",
   "metadata": {},
   "source": [
    "![image.png](attachment:98ee898a-a2a4-4f23-824e-efe81299cc10.png) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "88410c77-55f0-4483-b781-66427545014a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle X =x$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/latex": [
       "$\\displaystyle Y =x + 3$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X=MyEq(x,'X')\n",
    "Y=MyEq(x+3,'Y')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "98d08db6-dcd5-48c8-b2ce-976061d55728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\sqrt{x} + \\sqrt{x + 3} = B \\sqrt{x} + \\sqrt{A + x}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Q2=MQ(sqrs(X)+sqrs(Y),Q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "9d05e221-217d-493b-a23e-a14b4eb4e038",
   "metadata": {},
   "outputs": [],
   "source": [
    "# then...  A=3,B=1"
   ]
  },
  {
   "attachments": {
    "73517cb3-98da-4c40-8d77-21db4972fcb9.png": {
     "image/png": "iVBORw0KGgoAAAANSUhEUgAABUoAAAAnCAYAAADZ7XK3AAAFkklEQVR4nO3dPY7iXBYG4OPRtxSokVq9AlgBNUlHk04GYZF01tIkk3UCISyhok4aVlCsoNRBm73cL7DB/BlcP1NUtZ9HOhLC2BxfZ6+u780iIgUAAAAAQIv949oNAAAAAABcm6AUAAAAAGg9QSkAAAAA0HqCUgAAAACg9QSlAAAAAEDrCUoBAAAAgNYTlAIAAAAArScojWEsUoqUUuST3rWbeSPVPS+GTz+nPeMEAAAAQFs0CkqHiyIgOyyBWXN1Y1jUIhrnlQAAAADAq7sQlBazCGeDiFhPo59lkWVZZFk/puuIzt2DsPSp9sYxi9EyImIQsyfN7gQAAAAAXtPZoLQ3+RqDiIhYxqg7jtX2yCrG3SLo645XdafTwPx2E5ZGDGZmlgIAAADANZwNSj/fdIoP69/x+BbdtNT8f9NYR0RENz6ZoAsAAAAAb+5sUPr4u4jvonMTnxtfsheTvOk6nLubClWft5VPonfwu+Njp66Xx6R34pxnrQVacz8n//+lOnGzHehT/df9d92YN1lH9hrj9NrPHQAAAABeLtXXMC1SKZ+k3tnfRoreJOXFj9OkV30/rC6y9/3e9feO99IkT0cWw4NjRz3VXS9Srzqptod80tu/n6rxvWPV14s0vDQmh+ecGsfq4E5vh/dS81/bMU8pLYY1Y3F47rXH6bWfu1JKKaWUUkoppZRSL65LPzgItfbCuKZVF7KdCfN2A8DD0G7nWBGiNbhe1IWVl3s7CgZ3Q7uG43EuKL3U13Fo2aTHc302HKeac14+Tq/93JVSSimllFJKKaWUelld2PU+ImIet1kWWb9cR3Mwe8Yr0I9RvcV/+iX+5eg25rtfrH5FXn5cT/8Te3tGre7jZ3m9bs2inkfXi4j5j+WmictLCQy/bDey+n60YdUqxt83OzB9ecEGTMXr6rNB8T/7G2ZVju6/UY9Fn/ebgarp8+w4Nbm3F47Taz93AAAAAHiOBkFpaTWObpZFlvVjuo6Izl08pBSLj7RN++Pvxpsm9T51iw91G1k94Vp7ynFLKUVKD3HXiVhP+5Flx4HlRv7rVAgaMfwyON9jRKzufz69z/cwTgAAAADwhpoHpVurGHez6E+L+GswO974Z7g43NSnCAQ/ks83ZcN7weZOPdzFs25pPY1+lkW2U92Ts0GfIP91cibqW/i/jRMAAAAAvKFnBKWF1fh7FC9VD+LLJintTSJP5avky9FOGFjOQv2ITgSb+9U9/Vr8W+p+uv5O8B9hnAAAAACgxrOD0lOG38rZg+tp9G/rXiS/os835ezGPGreZt/artP5jj1WC7/Wrrna+/e/ymfyM+6bBpV/2DgBAAAAwCXPD0q3m/is4/fh4pRXfBV843hJgF5MvpZrei5/1K4HujX/UcyY7dzFt3e6DuvurN6vk1NzSofxrVzzYP3z/uQzacM4AQAAAMAl9UFp+Rp9SinygxCuN8kjzcqYdGdn8mq39Fm1yVNvEvlV1igdxCzlsWl9uNj0sIxRo9mu87gdlTHk7HjTqu06rPnkiq+9Vz127h4OntMwFmlWhNnL0Zl1UP/scarWy63u8VrHAAAAAHi/6oPS1Ti62SiWUYRwuxv0PNx1ImIZo8ONiOa3ke2EZtffzKcTdw9FH7NBlOto1u8uf2R+G1k5Btv7SdX11tN+ZN3xdWfP7vS4/5yKkHQ5yiK7GHi2YJwAAAAA4IwsItK1m3g91SzK5SiL97hMKgAAAADw/rzqZk4AAAAAAB+RoBQAAAAAaD1BKQAAAADQen/YGqUAAAAAAE9nRikAAAAA0HqCUgAAAACg9QSlAAAAAEDrCUoBAAAAgNYTlAIAAAAArScoBQAAAABa76/0339euwcAAAAAgKsyoxQAAAAAaD1BKQAAAADQeoJSAAAAAKD1/gaSxEAO96KMIgAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "c49c97ca-b5c3-4b2e-b9a1-5c546d33d394",
   "metadata": {},
   "source": [
    "![image.png](attachment:73517cb3-98da-4c40-8d77-21db4972fcb9.png)"
   ]
  },
  {
   "attachments": {
    "3f39920f-0580-4eb1-9ba2-a27aef98baec.png": {
     "image/png": 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UHBxMUVFR1L17dwJA/fr1o8LCQh1GrNyqVasIAH388cdy6zZs2CD8rnp6elJUVBSJRCICQEuXLtVBtMotXbqUWrRoIbNszZo19MYbb5ChoSFFRUXR6tWrhfNxdnamf//996XGmJycTJ6engo/o318fCgjI0OmfVpaGhGRwooqEomEEhISKCEhgZo3b05NmzalvXv3Unp6usLjrly5kpo2bUpNmzalWbNmUUJCAt2/f7/GmEtLS0kikShcFxwcTAC08veCMfbq01kiPWzYMLkPXWWJtJmZGfXs2VPmERkZSVlZWULbqn9MvL29heVFRUX09ttvEwAKCwujysrKWsWdk5NDERERwrHatWsnF1vPnj3J2tqajI2NKTw8nMrLy2t1zBfNnj1bOH5paalW993QaDOR9vPz02hbZYl0SkoKGRgYkIuLi5A8SNv7+/sLiUbVdbrk7+9P48aNE95TJSUlZGVlRQAoPT2diouLiYgoLy+PYmJiCAANHz5clyErtWrVKjI0NJRJjCsrK2nJkiVkYmJCM2bMoPT0dMrNzSUiooyMDHr//fdJJBLR3LlzqaysTFehC+7cuUPm5uYUFxcnLMvMzKSuXbtSs2bNhPebRCKh9PR0Cg0NJT09Pfrxxx9fapylpaWUnp5OAwcOFD7/pBc1QkND5Tr7hw4dIiL5RFqdTltddlClJTWDg4M13gdj7PWhs0Q6NjaWli9fTh07dqwxkV6zZk2N+5Mm0j169KA7d+7IrJPWB9ZW4rl27Vphf3v37lXYJi4ujgwNDQkA5eXl1fqYVUkkEk6k/0sbifSNGzfIy8tL40Ra+t57MZEeM2YMtW/fXmEt3ePHjwuvYUREhEbH1aYjR45QixYtZK7glpSUKK3de+fOHfLx8SEHBwfhW6H6ZNWqVWRtbS2zTHo+enp6CrfZv38/NWrUSOg46FpqaioBoJMnTwrLLly4QK6urjRhwgSF2xgZGdFbb71FJSUlLytMhWbNmkUAKDw8XG5d9+7diYg07rTVdQdVmkg7OTlptD1j7PWiszHSw4cPx6effgo3N7ca2w4dOlTl/V65cgVDhgwRfs7Ly0N+fj4AYNWqVVqpq9qsWTOIxWKMHj0affr0Udhm0KBBWivJpsinn35aZ/t+3dy/fx8XL17UePs9e/agadOmCstm3b17F9evX5db3qVLF0yaNAkeHh74v//7P5WPdfPmzTqZfGZnZwdnZ2csXLhQWGZsbIyffvpJYY3uxo0bw87ODo8fP8aDBw80OmZOTg7Onz+vcczKZGZmIjw8HK1bt1a4nohw69YtueVubm51+jurLkUxenl5Yd++fXBycpJbd/v2bRAR9u3bV+ux3ikpKbh3755G2964cQNnzpxBly5dYGtrq7SdmZmZTNm7x48fAwDs7e2FCa+NGzeGr68vfHx8cObMGRw7dgxhYWFo27Ytdu3aBQcHB2F7S0tLLFmyBABw6tSpau9OyBhj2lIvJhtqU2FhIW7evInff/8dALBv3z4kJCTAw8MD/fv318okkJYtW6JJkyYwNzeHqalprfenifo80UsXpJMOa+P999/XeNt33nkH/v7+cstLSkpQWFgot/zhw4e4dOkSjI2NYWVlpfJxpk2bJjPBVlv27t2LlJQUmZvR6Onp4cMPP8SYMWPk2v/777/YtWsXvL29Fa5Xxa5du+Dn56dxzMpUVlYiLy8PkZGRMssNDQ0xevRoAFDYcYqIiMDTp08xZMgQ4bbnuvT555/D399frhxb69atFb4H5syZg4qKCowYMaJWFwxOnjyJgIAAmU6VOtq2bYu///4bZ8+exeTJk5W2q02nTdsdVMYY01SDqAvVt29fuStFgYGBGD9+vHBFOygoCFu2bMGZM2fw7NkzbN26Fa1atRKu3AYEBMDDw0Mr8Zw7d67aWekAkJaWBolEghYtWkBfX76/kpWVJVclok2bNnKlx3Jzc+WSZkdHR3Tt2lXmj05BQQHu3r0LMzMzhVfibty4gbKyMpljPHr0CJmZmXJtraysFNZSvXLlilCRxN7eHk2bNq32fEQikUrfOGiDNmoFBwYGqr1Nbm6uwkQZAFasWIH58+crvCp34sQJnD59GsOHD1f7mNpWXl6OjIwMODo6qtT+wYMHmDp1KsLDwzF+/Pg6jk57DA0N8f333yM8PFzufXn06FH89ttvMDMzw9ixY+tFIg0APXr0QIsWLaptc+/ePezfvx9xcXHw8PBAUFBQrW5wcufOHeTm5mq8fXW+//57XLp0CQAUdtoUkXba+vTpgzFjxuDPP//UegeVMcY0puOhJTRq1CiVqna8+eabFBYWJkwoAUCtWrWSab9mzRqFM8dHjRql1ZilY6Q7d+5MN27ckFufnJwsjP3euHGj3PpvvvmGevXqJRfn559/LtOusLCQBg8eLKw3MDCgwMBAGj16tNwY6f/5n/8hANSnTx+54x06dIiaNm1KAOjixYtERJSfn08BAQEKn6+OHTtScnKysP38+fMpLCxMGPMNgAYNGkSbNm0iIqIHDx4oPB8rKyvav3+/5k+0ClQdI/3rr78qXXfo0CECIDN5VVXfffcdiUQiio2NVXmbuLg4EovFNGDAALXHzw8cOJCCgoLUDbNaaWlpBICOHDmitM3Vq1cpLCyMwsLCyMvLi1q3bl3rqgYbNmwgU1PTWu1DkRUrVtR4Pi+S/v707dtX6/Fo4siRI2Rra0uzZs1S2mbr1q0UFhZG7dq1IwAUGBiotYnNffv2pUmTJmllX1UtXbpU4Zh7ZdLS0sjFxYXCw8OFahzp6el0/fp1evz4sVz7bdu21XoSLI+RZoypo14n0klJSWRlZUUDBgyg7OxsIiLKysoiPz8/AkBGRka0fPlyoX1paSlNnjxZLqFzdHTU6uSh1NRU8vDwIAC0YcMGun79Ok2YMIE8PT3J09OTHB0dydbWlpKSkoSqAETPK4jMnj2bzM3NKTw8nC5duiQ8QkJCZM4nLy+PAgMDydLSkrZs2UKXLl2iy5cvU35+Pl28eJHs7OzI1tZWqC6wdetWsrS0VJhIZ2ZmkrOzs0wi/eDBA2rbti1169ZNiOHo0aPUqVMnMjc3p4MHDxIR0cyZM4UJcdJ2nTp1IktLS2FyXlFRkcy5SB9vvPEGWVtbU3x8vNae+xcdOHCg2s5SamoqeXp6koWFBX366acK20iTcUWJdE5ODl2/fp1ycnIUbvvdd9+RhYWFyvHu2rWLmjRpQm+99ZbwnlaHpol0dna20koUp06dqjHxjI+Pp7Zt2woPCwsLWrNmjUqlxpTRNJFOTU2l69evKz0fHx8fsrKyUmkCakFBAYWEhJC+vj7NmzePbt26pXY8mkpNTVXakVqwYAE5ODjIlY6ravLkycLrYWdnRy1btqTx48crTDDVNXToUI0m6z18+JDu3r2rcF1ZWRmFhoZS8+bNq92Hpp222nRQq+JEmjGmjnqdSBMR7dmzh/Lz82WWXbt2TdgmNDRUWJ6dnS0s79ChA7m4uAg/e3h40JUrV7QS84kTJ8jR0VHh1Vzp4+eff5bb7p9//iEAtGjRIrl1CxYskDmf1atXU6NGjZRe6dyxYwe99957MlegPvroI4WJNBGRm5ubTCKtiLQ+tTRRu3r1Knl6epKrqyudO3dOpu2uXbto/fr1SvdFRHTr1i0CIFcHV5ukf/QUJU3nz58nV1dXmffEtWvX5NpZWlpSQEAAPX36VGb5t99+S/369SMANGfOHIXHVzeRbtq0KQ0YMICePHmi8jZVaZJIr1mzhvz9/ZXWSPbx8VH7Cm5QUJDwrZAmV6aLi4tp+PDhZGRkRLt371Z5uwMHDpCFhQUBoJs3byps4+PjQ//5z39U2p+0ZnCrVq3o1KlTKsdRGytWrKCIiAgyMzOjlStXyq3Pycmh/v37U+vWrVXe56VLl6h9+/YEgEaOHKlWNZ/jx49TRESEzMPDw4MiIiIoNTVV5f2sXLmSfH19ycHBgU6cOCG3XlqFpKbPA006bbXtoFYl/UxRpVoUY4zV+0RakRcT6fLyclq7dq0wnMLJyYnu3LlDN27cEBJUALRq1SqlRfjVsX37djI3NyexWEwbNmygpKQk4TF27FgCnt8Y4cUSVD169CAAdO/ePZnlZWVlNHPmTDI0NKSIiAjKysqili1bypXvkpJIJLRu3Tq58ne1SaRv3rxJTk5OtHr1arp9+zaVl5dTq1atCABNnjxZpeclLS2NFi9eTN7e3uTt7S3cpMHGxqbObjxSXSK9bds2cnJyIicnJ6Gs2fbt2+XaWVpa0rp16+SW9+7dm5ycnMjIyIhsbW3pn3/+kVmfl5dHjo6OKiXSu3btIm9vbxo8eDA9fPhQpXPbsmWL8FxKHxYWFuTo6Eh+fn7CMn9/f0pMTFS4j8jISDIyMiIA1L59e7lOKdHzxPO9996T60hUJzExkcRiMQGgqKioGttnZ2dT//79qXv37hQYGEjvvPOOzDdGgYGBwvksWbJE4T6uXr1K3bt3J1tbWwJAgwcPljufn376iSwsLGj+/PnVxlNYWEj/+c9/SE9Pj5o2bVptB1Nq+/btFBgYSG+++aZwHr6+vnKvUe/evZV+Q/L111+TgYGBcO4ODg506dIlmTbSzzcfH58aY6rq1q1bwr5VfS3T09OFb9defIjFYurfvz9FRUXRjBkzaODAgcI3VS9atGiRzNCvFi1ayCW+0kS6U6dOap2XKp222nZQq+Ir0owxddTrRPrBgwe0fPlyWr58uczVoqqJdJ8+fej06dMy43uvX78utD179iy1adNGbkxxbUjHSE+cOFHheunNZn755ReZ5c2bN5dJpDdu3EjLly8Xaq5Kr6JJx6xWl0grOp/qEunQ0FClifS5c+fIxcWFPD09hSu25eXlwjEqKipqeEaej+mUjsMODg6mmTNn0syZM6l3794kFovpjz/+qHEfmpD+0Zs7d2617YYOHUoAaNy4cXI35VGWSEu5u7sLf8irkn4D8sEHH1R77Pj4eBKJRNS/f38qKCio4Yz+v8TEROF5rPqIiYmhTZs2CT//8MMPSvcRGxsrtLO0tKSBAwfKDFM5ffo0OTo6qnwFtyrpMCpVEmnp+YSFhRHR8+FAAwYMIENDQ4qJiaGKigohzppumnT37l3q1q0bAfJ1ipctW0YWFhZ0+PBhpdtLJBLhjqetW7dWuwb5oUOHaMGCBUREFBUVpfD1UebXX38V2kk7d9K6ylJLliwhAHLfAqlC2mnaunWrWufz4jk4ODjIjJHevHkznTt3ji5cuKBwHzt27BC2lXawVqxYIdPmm2++IQBq33mxuk6bJh3UmnAizRhTR71OpP/8809hXdWrVFUTaTMzM5l2im4JXFc3ZBk7dqzCGx/ExsYS8PxuXFXPSZpId+nShXr27EktW7YkOzs76tq1Kx0/flxIslRJpKW3Kn8xkba2tpa5E5rUkSNHFCbSN2/epFatWpGjo6PMV+XqJNLDhg0je3t76tatGx0/flzmnJctW1anQztSU1PJ3NycHB0dq213+fJl4Xxe/Or3jTfeoMzMTKXb7tmzh8zNzcnY2Fjm615pIv3ibY6r2r17NzVr1owGDhyo0WTGF33yySf09ddfa7StdKjT0KFDhWXLli0jfX19hR2R3NxcmZtjvEjdRPpFtZlsuGDBAjIwMKCWLVvKjGtetmwZWVtb0+3bt5Vu+/nnn5OJiQktXbpU4VCfl0U6lEosFtO6deuEYVqbNm2i4OBguU5XRUUFbd68mfbt26d0n9JEOiAgoFaxDRkyhM6cOaPRttI5B6ampjKdvE6dOmmUSBMpfq9p2kGtCSfSjDF11Os60tXVIJWaMmUKvL291d733r17NQlJxsWLF3H79m255a1atYKbmxsSEhIU1kXt0KEDvL29cfbsWWRkZCApKQm+vr4Qi8UqH1vRcQHAw8MDgwYNklseGxursP348eMhFotx8OBBtGnTRmGbmp6rc2CxEgEAAAucSURBVOfOISMjA9u2bYOvr+9Lra3t4uKCL7/8ssZ27du3x8CBAwEAH330kbD88OHDaNSoUbU3jhgyZAg+++wzlJWVITY2FllZWQBUew+NGDECOTk52LFjB2xsbOTWq/s+TE5ORmpqqlrbSL399tsAnt+s4uTJk8JyOzs7LFiwQK79hx9+iBYtWiA+Pl6j49WluXPnwtnZGWlpaSgpKZFZZ2xsjFatWincLiUlBfHx8Rg8eDA+++wztG/f/mWEq1Dfvn3h5eWFwsJCTJ06FXfv3gUALF++HA4ODnKfB7m5uZgwYYJQC7suFRYWYv369Rptu3v3bnTu3BnFxcX4/fffkZeXJ6zr3Lmzwt+DvLw8ZGRkyL2WyuzZswcffvgh+vXrh61bt6r12ckYY9qk00S6rKwMZWVlws+5ubkoLS0VfpZ+OLq5uWHs2LEAgOLiYsyZMwcAoK+vD1NTU+Ff4PmHeFJSkswxpk2bJrO/JUuWIDg4GH379sUnn3yicfw9e/aEu7u73HIvLy+hrnFkZCQKCgpkjq+np4c1a9agWbNmMts9fvwYRUVFwvlIJBKFtVILCgrwww8/KIzpwoUL+OOPP+SWK6p7/dtvv+Hq1at466230LZtW2F5aWkpKisrsXDhQohEIqXHkt70Ijs7W+H6yspKFBUVCf/WpYcPH2LdunVK1xsYGODjjz+GSCTCs2fPhPfdtm3bVPrjPW7cOLi4uODvv//G5cuXAQA//PADjI2NFd4Nr6ysDHPnzkVFRQWmTp2K4uJiPHr0SObxzTffICIiQsMzVt/ixYsxbtw4PHz4EGPGjMFff/1VY7Lk5+en8D1++PBh/PXXXzA0NISJiUldhVyt+fPnA3ieVBcXFyM9PR3r169XmlQ9e/YM7777Li5duoRp06ahrKwMubm5cq+LqslcbbVp0waDBg0S6szPmTMHjx49AhHJ1ZOvSiKR4NGjR3j27JmwrKysTNjWzMwMX3/9tcZxxcbG4sKFCxpv7+zsjB07dsDe3h579+7FxIkTER0djdTUVPTv3x/Ozs5y26jbadN2B5UxxjSmq0vh+/bto0mTJslNcAkKChKGK0jrSDs5OVF0dDRFR0fL1FWuOmZ19erVwvLp06cL7SdOnCi0lX6lKJ2pDyiuu1ydoqIiGjNmDAGgXr16CbWUX3T48GHha1bpBLcbN26Qp6encD7SMlV5eXkUHR1N7u7utGPHDiJ6Pm7R1taW/P39ha9Hy8vLKTo6mjp37izEv2fPHuGYW7ZsIWNjY3rvvfcoOjqaLly4QDExMRQdHU02NjYEQCivt3PnTho5ciTZ2NgI2ycnJ1N0dDSNHz+edu3aRUTPh9506tRJeD6Tk5PpwYMHFB0dTa6urjR58mQyMzMjAPTtt98K+zp79qww/AQATZs2Ta3nWR2LFy8mADRjxowa20qHEm3ZsoXu3btHvr6+9MYbb6h0HOlYdulQld69eyscSkT0fMzoi+9tRY8uXbqofqJU+zrSu3btIisrK5kYgoODFbZduXKl0CY6Oppu3rxJd+7coejoaDI2NiYAtHDhQo1jqW0d6fv37wu/C2+//Tb9+++/BIBOnjypsP3u3btlznvixIkyE/+kD02Hqmhq/PjxMsdv166dwnZPnjwRSn8CoJCQEOH38qOPPiLg+cTN48eP1yqev//+m+zs7GpdR/rjjz+WOS9zc3P6/fffFbYdPHgw+fn5ydSvlzp06BDZ2dmRoaEhlZaW0pw5c0hPT4+mTp1KWVlZlJOTI/NYsWIF+fr6ahy3dGhHdbXnGWNMSieJdEJCAtnZ2cl8yJqYmJBYLCaxWCzUAM3Ly6MxY8aQqampTFtTU1MKDg6WKdd19+5d+u2334R9SNsaGhqSWCym8+fPC20/+ugjod2hQ4fUij0rK4vEYrGQPDZp0kRhu3HjxhEAMjY2JkdHR6GWcnJyMjk7O5ORkRH5+flRQEAA+fr6kkgkoh9//FFmHwcPHiRjY2MyMDCggIAAevPNN4XzkT6GDBkis42jo6OQwLdt25bMzMxILBbT/PnzhW02btwo/EEWiUQUEBBAAQEB5OXlJexfmqBfuHCBLCwsyNDQkExMTMjd3Z369OlDYrFYuNnKxo0bycjIiMRisbAvd3d3+u6772jKlClkZmZGLVu2VKkygiZu3bpFrq6uKiXSFy5cID09PfL09KQ//viDAKicSN++fZtEIhEZGxtTQEAANW7cWGkiHRsbK/M6KXtIOyyqGj58uMpVVJT59ddfSSQSCb8jyhLPiooKmjNnjhCrr68v+fv7Cz+HhoYqreWsis2bN9dYU7gm4eHhpK+vTwDIy8ur2vMZMWJEja+Hj4+PXFWdupafn0/jxo0jPT29ahNpouedhz/++EMubkNDQ5o7d65GExQVGTVqVK3LhT558kSoYoT/TuxURtVOW111UKuSJtK1veEQY+z1oLMr0qtWraLg4GDhcezYMaVtb926JdP2wYMH1e67uLhYaPvdd99pO3Qien4jh+DgYKXJYXR0tFyyX9X27dtlzknZlZrDhw/LtHvxfBRdPduyZYvQft68eTLr5syZQ9u3b6ecnByZ/QYHB9OmTZuUXo2Ljo6mpKQkCg4OpsLCQrXOJzc3l4KDgxVebdKWrl27UkBAgEoT+qSJ19SpUwmQr/xQnbi4OLK2thY6SZs3b65N2DpTtSykssSzoZBWVWno5yOdDFpdIq1IZWUlrV27to6iqp2dO3eSpaVljYm0qp22uuqgVhUYGEhmZmZKK5QwxlhVOq/awZg27Ny5kwwMDGjQoEE1tv3yyy9lEi9FtZWrI72BibKqKg1BSkoKtW3blkaOHFmru8DVB1u2bBGGaOjr62tUFaI+2LhxI4lEIoU3c2rIfv75ZxKJROTm5qbrUFTi6elJs2fP1nUYjLEGQo+ISOkAasYakG+++QbLli0Tqmook5SUhFGjRuHevXsAgPz8fFhZWal8nNDQUKxYsQLW1tbIycmpVcxMOxYuXIivvvoKoaGhiIyM1HU4rIH68ccfERISAgcHB/z1119KKxkxxpiUoa4DYOxl69atG/z8/IREWl3h4eHIy8vDnj17tBwZ09SIESPQvn17uLq66joU1oDdvXsXRUVFePfddzmJZoypRO+/d8lj7JUQGhqKkpKSakvhAUBUVBRmzpwJiUSCvLw8ta5IM8Z0R09Pr072W1lZiblz5+Lnn39GQkKCTElQXanLL4zr6nlk7HXDQzvYKyUrKwu9e/dGbGwsPDw8qm27fft2VFZWYuTIkRCJRC8pQsaYpjT5c6Vqwnj58mV07NgRrq6uuHHjhtrHYYy9nnhoB3ul2NjY4PLlywpvkvKi99577yVExBjTlrq8ilpeXg4A+OKLL+rsGIyxVw9fkWaMMfbac3Nzg0gkQlxcHBwdHXUdDmOsgdDpLcIZY4wxXYuJiUFGRgZGjBjBSTRjTC08tIMxxtgrr7ovX69cuQInJyeEhYVpbYIfT+Zj7PXAiTRjjLFXnrLE9vbt29i9ezdmzJjByS9jTG08RpoxxthrSyKRoLy8HCKRiBNpxpjaOJFmjDHGGGNMAzzZkDHGGGOMMQ1wIs0YY4wxxpgGOJFmjDHGGGNMA5xIM8YYY4wxpgFOpBljjDHGGNMAJ9KMMcYYY4xpgBNpxhhjjDHGNMCJNGOMMcYYYxrgRJoxxhhjjDENcCLNGGOMMcaYBjiRZowxxhhjTAOcSDPGGGOMMaYBTqQZY4wxxhjTACfSjDHGGGOMaYATacYYY4wxxjTAiTRjjDHGGGMa4ESaMcYYY4wxDXAizRhjjDHGmAY4kWaMMcYYY0wDnEgzxhhjjDGmAU6kGWOMMcYY0wAn0owxxhhjjGmAE2nGGGOMMcY0wIk0Y4wxxhhjGuBEmjHGGGOMMQ1wIs0YY4wxxpgGOJFmjDHGGGNMA5xIM8YYY4wxpgFOpBljjDHGGNPA/wPCAh3+nJoX1gAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "965aeff9-1187-4fbf-a9f3-7b35535f3666",
   "metadata": {},
   "source": [
    "![image.png](attachment:3f39920f-0580-4eb1-9ba2-a27aef98baec.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "271eaf9a-7624-4175-8f6f-f4a577b44acf",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# This scrip initializes all variables. \n",
    "import sys\n",
    "sys.path.insert(0, './Libaldo')\n",
    "from Libaldo import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "55ef427a-375b-4359-80d8-69d047d2cb6f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append('Libaldo')\n",
    "from  libaldomath  import *\n",
    "# this cell will be initializing your variables"
   ]
  },
  {
   "attachments": {
    "c2300ab4-99ef-4896-812d-34baf9813c34.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "5db18a00-d570-4c30-a522-3065d4c7bac8",
   "metadata": {},
   "source": [
    "![image.png](attachment:c2300ab4-99ef-4896-812d-34baf9813c34.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a34446ae-0bb7-40f8-8748-4147c3500464",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A = \\sqrt{\\sqrt{3} + 2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P1=MQ(A,sqrs(2+sqrs(3)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "94d61fcb-3243-4150-8edc-0e2d9ae3e7a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A^{2} = \\sqrt{3} + 2$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P1.Pow(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "c60cd806-c8fd-48fc-b225-982cdc95bc67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle 2 A^{2} = 2 \\sqrt{3} + 4$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P1.Mul(2)"
   ]
  },
  {
   "attachments": {
    "98ee898a-a2a4-4f23-824e-efe81299cc10.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "b183084d-d450-4cca-8aef-aebba44180d4",
   "metadata": {},
   "source": [
    "![image.png](attachment:98ee898a-a2a4-4f23-824e-efe81299cc10.png) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "50c78943-5799-46f4-a4f7-b7c525e17c7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\sqrt{2} A = \\sqrt{2 \\sqrt{3} + 4}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P1.Rpow(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "efb3070a-c180-470b-8e1d-5d7450355807",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle \\sqrt{2} A = 1 + \\sqrt{3}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "P1.setR(sqrs(3)+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "eb47d940-e640-462c-b503-693a865dbb89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle A =\\frac{\\sqrt{2}}{2} + \\frac{\\sqrt{6}}{2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "A=P1.solve(A)"
   ]
  },
  {
   "attachments": {
    "09a93a88-7116-47cf-b7d0-9e2a8cd46cad.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "9e6fd145-7d5b-4bbb-8cb7-b3c354cc6d09",
   "metadata": {},
   "source": [
    "![image.png](attachment:09a93a88-7116-47cf-b7d0-9e2a8cd46cad.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "a019f956-f379-4902-9048-a65e60ca26c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\displaystyle B =- \\frac{\\sqrt{6}}{2} + \\frac{\\sqrt{2}}{2}$"
      ],
      "text/plain": [
       "<IPython.core.display.Math object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "B=MyEq(sqrs(2)/2-sqrs(6)/2,'B')"
   ]
  },
  {
   "attachments": {
    "6808bb70-3804-4cdf-895b-5a8e53ae0d94.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "cf580bd8-5177-47a1-9b17-dbdfc0a293e6",
   "metadata": {},
   "source": [
    "![image.png](attachment:6808bb70-3804-4cdf-895b-5a8e53ae0d94.png)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}